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Abhinay45
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whisper-tiny-us-ZA

Automatic Speech Recognition
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whisper
Generated from Trainer
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metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: whisper-tiny-us-ZA
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: PolyAI/minds14
          type: PolyAI/minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.27835051546391754

Visualize in Weights & Biases

whisper-tiny-us-ZA

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6915
  • Wer Ortho: 0.2821
  • Wer: 0.2784

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 5
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.3413 3.125 100 0.4281 0.2727 0.2474
0.0659 6.25 200 0.4672 0.2754 0.2526
0.0076 9.375 300 0.5252 0.3035 0.2899
0.0019 12.5 400 0.5568 0.2874 0.2758
0.0009 15.625 500 0.5804 0.2901 0.2771
0.0006 18.75 600 0.5947 0.2861 0.2732
0.0005 21.875 700 0.6062 0.2848 0.2745
0.0004 25.0 800 0.6170 0.2834 0.2745
0.0003 28.125 900 0.6261 0.2834 0.2745
0.0003 31.25 1000 0.6346 0.2781 0.2719
0.0002 34.375 1100 0.6423 0.2794 0.2732
0.0002 37.5 1200 0.6497 0.2794 0.2732
0.0002 40.625 1300 0.6563 0.2794 0.2732
0.0002 43.75 1400 0.6627 0.2794 0.2732
0.0001 46.875 1500 0.6680 0.2941 0.2874
0.0001 50.0 1600 0.6736 0.2874 0.2809
0.0001 53.125 1700 0.6781 0.2874 0.2809
0.0001 56.25 1800 0.6833 0.2874 0.2809
0.0001 59.375 1900 0.6876 0.2834 0.2796
0.0001 62.5 2000 0.6915 0.2821 0.2784

Framework versions

  • Transformers 4.41.0.dev0
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.19.1